big data integration

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2019 Predictions for Customer Data Management

Published By: Google - SAP     Published Date: Nov 01, 2019
"Report: 2019 Predictions for Customer Data Management Where will the next evolutions in customer experience, consumer privacy and the digital enterprise lead your business in 2019? In this report, we break down the hottest trends, biggest roadblocks and most tantalising opportunities facing the customer data management market. Download it now to explore megatrends that we see as being vital considerations if you want to thrive – not just survive – in today’s and tomorrow’s digital marketplace. You’ll discover: Forecasts for the future of data protection and consumer privacy regulations Predictions about cutting-edge technologies such as artificial intelligence, machine learning and customer data platforms New frontiers ushered in by evolving cloud technology integrations and the convergence of the front and back offices"
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Google - SAP

360 Degree Marketing Intelligence: The Ultimate Guide to Integrating CRM and Google Analytics Data

Published By: MoreVisibility     Published Date: Dec 19, 2017
As the approach to strategic business decision making becomes more and more data driven, a method for consolidating our various data sets, which are often spread across multiple systems becomes exceedingly important. Two of the biggest players in data driven decision making are website analytics platforms and customer relationship management systems. The former includes accumulating data on top of the funnel behavior such as site traffic origins, lead generation, content consumption tracking, device usage, and overall site behavior. While the latter has a focus more on bottom of the funnel activity such as lead nurturing, customer status, lifetime value, etc. Lastly, without communication between these two essential platforms, a complete understanding of your customers, from lead to longtime client, may never be possible. A web analytics (Google Analytics) and CRM integration provides you with a 360 degree view of your customer base, so that you can understand not just what PPC efforts
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MoreVisibility

451 Research: SAS Data Loader for Hadoop

Published By: SAS     Published Date: Apr 16, 2015
SAS Institute is gearing up to make a self-service data preparation play with its new Data Loader for Hadoop offering. Designed for profiling, cleansing, transforming and preparing data to load it into the open source data processing framework for analysis, Data Loader for Hadoop is a lynchpin in SAS's data management strategy for 2015. This strategy centers on three key themes: 'big data' management and governance involving Hadoop, the streamlining of access to information, and the use of its federation and integration offerings to enable the right data to be available, at the right time.
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SAS

Aberdeen Customer Derivative

Published By: Adobe     Published Date: Nov 07, 2013
Aberdeen's Insights provide the analyst's perspective on the research as drawn from an aggregated view of research surveys, interviews, and data analysis.
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adobe, aberdeen group, analyst insight, technology tools, buying behavior, customer experience management, cem, buyer interactions, customer engagement programs, adobe customers outperform, company brand awareness, big data, structured data, data quality, data integration, customer segmentation, customer empowerment, quality of service, content management
    
Adobe

Addressing customer analytics with effective data matching

Published By: IBM     Published Date: Nov 06, 2014
With the advent of big data, organizations worldwide are attempting to use data and analytics to solve problems previously out of their reach. Many are applying big data and analytics to create competitive advantage within their markets, often focusing on building a thorough understanding of their customer base.
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big data, data integration, analytics, customer matching, ibm, networking, data management, data center, research
    
IBM

Analytics: The real-world use of Big Data

Published By: IBM     Published Date: Jan 02, 2014
This study highlights the phases of the big data journey, the objectives and challenges of midsize organizations taking the journey, and the current state of the technology that they are using to drive results. It also offers a pragmatic course of action for midsize companies to take as they dive into this new era of computing.
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ibm, analytics, global business service, big data, business value, it professionals, volume, velocity, variety, customer analytics, trends and insights, information management, data security, integration, variety of data, analytic accelerator, infrastructure, data management, identity management, application integration
    
IBM

Application Integration in the World of Mobile, Social, Cloud, and Big Data

Published By: TIBCO     Published Date: Apr 29, 2014
Learn about the new IT landscape as it relates to the new integration and see why the need for a comprehensive integration strategy has never been more urgent than now.
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mobile, social, cloud, big data, tibco, comprehensive integration strategy, networking, it management, enterprise applications, mobile computing, cloud computing
    
TIBCO

Back to basics: Fundamentals of test data management

Published By: IBM     Published Date: May 28, 2014
The right test data management solution accelerates time to value for business-critical applications and builds relationships and efficiencies across the organization. IBM InfoSphere Optim Test Data Management closes the gap between DBAs and application developers by providing all teams with accurate, appropriately masked and protected data for their work. Developers can confirm that new application functionalities perform as expected. QA staff can validate that the application performs as intended based on the test cases, and that integrations work properly. And business leaders can be more confident that competitive functionality will be delivered on time with less risk.
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ibm, ibm infosphere, ibm optim solutions, ibm test data, test data management, dba, database management, big data, applications, business critical applications, integrations, it management, data management, business technology, data center
    
IBM

Big Data Integration and Analytics for Cyber Security

Published By: Teradata     Published Date: Jul 07, 2015
As cyber security challenges continue to grow, new threats are expanding exponentially and with greater sophistication—rendering conventional cyber security defense tactics insufficient. Today’s cyber threats require predictive, multifaceted strategies for analyzing and gaining powerful insights into solutions for mitigating, and putting an end to, the havoc they wreak.
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Teradata

Big Data Integration and Governance Considerations for Healthcare

Published By: IBM     Published Date: Aug 05, 2014
There is a lot of discussion in the press about Big Data. Big Data is traditionally defined in terms of the three V’s of Volume, Velocity, and Variety. In other words, Big Data is often characterized as high-volume, streaming, and including semi-structured and unstructured formats. Healthcare organizations have produced enormous volumes of unstructured data, such as the notes by physicians and nurses in electronic medical records (EMRs). In addition, healthcare organizations produce streaming data, such as from patient monitoring devices. Now, thanks to emerging technologies such as Hadoop and streams, healthcare organizations are in a position to harness this Big Data to reduce costs and improve patient outcomes. However, this Big Data has profound implications from an Information Governance perspective. In this white paper, we discuss Big Data Governance from the standpoint of three case studies.
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ibm, data, big data, information, healthcare, governance, technology, it management, data management
    
IBM

Big Data Integration and Governance Considerations for Healthcare

Published By: IBM     Published Date: Oct 01, 2014
This white paper discusses how IBM InfoSphere can support the integration and governance of Big Data in healthcare. The white paper reviews three case studies including predictive analytics with Electronic Medical Records, time series data in a neonatal intensive care unit and predictive pathways for disease.
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big data, data integration, healthcare, data management, business activity monitoring, business analytics
    
IBM

Big Data Integration and Hadoop

Published By: IBM     Published Date: Feb 22, 2016
Apache Hadoop technology is transforming the economics and dynamics of big data initiatives by supporting new processes and architectures that can help cut costs, increase revenue and create competitive advantage.
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ibm, data, big data, integration, hadoop, enterprise applications, data management, business technology
    
IBM

Big Data Integration And Hadoop

Published By: IBM     Published Date: Apr 18, 2017
Apache Hadoop technology is transforming the economics and dynamics of big data initiatives by supporting new processes and architectures that can help cut costs, increase revenue and create competitive advantage. An effective big data integration solution delivers simplicity, speed, scalability, functionality and governance to produce consumable data. To cut through this misinformation and develop an adoption plan for your Hadoop big data project, you must follow a best practices approach that takes into account emerging technologies, scalability requirements, and current resources and skill levels.
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data integration, data security, data optimization, data virtualization, database security, data migration, data assets, data delivery
    
IBM

Big Data Means All Your Data: Integration is Key

Published By: TIBCO     Published Date: Apr 08, 2013
As the volume of available data increases, and we have new ways of extracting insights from data, it is valuable to take a step back and examine the impact of these insights on integration and company actions. Join us for this webinar and learn how you can use big data in your organization.
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big data, integration, architecture, database, data warehousing, operations management, application performance management, best practices, business activity monitoring, business analytics, business integration, business intelligence, business management, business metrics, virtualization, cloud computing, infrastructure, infrastructure management
    
TIBCO

Big Data Means All Your Data: Integration is Key

Published By: TIBCO     Published Date: May 15, 2013
According to Forrester, most organizations today are only using 12% of their available data and only 37% of organizations are planning some type of big data technology project. At a time when companies are seeing volume of information increase quickly, it’s time to take a step back and look at the impact of big data. Join Mike Gualtieri, Principal Analyst at Forrester, for this webcast exploring the importance of integration in your big data initiatives. Discover how your ability to operate, make decisions, reduce risks and serve customers is inextricably linked to how well you’re able to handle your big data. Continue on to gain insight into: •3 key big data management activities you need to consider •Technologies you need to create for your big data ecosystem •A multi-dimensional view of the customer is the holy grail of individualization •Overcoming key integration challenges And more!
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big data, integration, architecture, database, data warehousing, operations management, application integration, application performance management, best practices, business activity monitoring, business analytics, business intelligence, business management, business metrics, business process management, enterprise software
    
TIBCO

Blueprints for Big Data Success

Published By: Pentaho     Published Date: Jan 16, 2015
If you’re considering a big data project, this whitepaper provides an overview of current common use cases for big data, from entry-level to more complex. You’ll get an in-depth look at some of the most common, including data warehouse optimization, streamlined data refinery, monetizing your data, and getting a 360 degree view of your customer. For each, you’ll discover why companies are investing in them, what the projects look like, and key project considerations, including tools and platforms.
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big data, nosql, hadoop, data integration, data delivery, data management, data center
    
Pentaho

Business Driven Governance: Managing Policies for Data Retention

Published By: IBM     Published Date: May 28, 2014
Different types of data have different data retention requirements. In establishing information governance and database archiving policies, take a holistic approach by understanding where the data exists, classifying the data, and archiving the data. IBM InfoSphere Optim™ Archive solution can help enterprises manage and support data retention policies by archiving historical data and storing that data in its original business context, all while controlling growing data volumes and improving application performance. This approach helps support long-term data retention by archiving data in a way that allows it to be accessed independently of the original application.
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ibm, data retention, information governance, archiving, historical data, integrating big data, governing big data, integration, best practices, big data, ibm infosphere, it agility, performance requirements, hadoop, scalability, data integration, big data projects, high-quality data, leverage data replication, data persistence
    
IBM

CITO Buyer Guide for Big Data Integration

Published By: Pentaho     Published Date: Aug 22, 2016
This white paper provides a concise overview of big data integration technologies, and reviews key things to consider when creating an integrated big data environment that blends new technologies with existing BI systems to meet your business goals.
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big data, data integration, bi systems, hadoop
    
Pentaho

CITO Research: Buyer's Guide to Big Data Integration

Published By: Pentaho     Published Date: Mar 08, 2016
If you’re evaluating big data integration platforms, you know that with the increasing number of tools and technologies out there, it can be difficult to separate meaningful information from the hype, and identify the right technology to solve your unique big data problem. This analyst research provides a concise overview of big data integration technologies, and reviews key things to consider when creating an integrated big data environment that blends new technologies with existing BI systems to meet your business goals. Read the Buyer’s Guide to Big Data Integration by CITO Research to learn: • What tools are most useful for working with Big Data, Hadoop, and existing transactional databases • How to create an effective “data supply chain” • How to succeed with complex data on-boarding using automation for more reliable data ingestion • The best ways to connect, transport, and transform data for data exploration, analytics and compliance
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data, buyer guide, integration, technology, platform, research, enterprise applications
    
Pentaho

Cloud For Dummies E-Book

Published By: Group M_IBM Q418     Published Date: Oct 02, 2018
Organizations are faced with providing secure authentication, authorization, and Single Sign On (SSO) access to thousands of users accessing hundreds of disparate applications. Ensuring that each user has only the necessary and authorized permissions, managing the user’s identity throughout its life cycle, and maintaining regulatory compliance and auditing further adds to the complexity. These daunting challenges are solved by Identity and Access Management (IAM) software. Traditional IAM supports on-premises applications, but its ability to support Software-as-a-Service (SaaS)-based applications, mobile computing, and new technologies such as Big Data, analytics, and the Internet of Things (IoT) is limited. Supporting on-premises IAM is expensive, complex, and time-consuming, and frequently incurs security gaps. Identity as a Service (IDaaS) is an SaaS-based IAM solution deployed from the cloud. By providing seamless SSO integration to legacy on-premises applications and modern cloud-
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Group M_IBM Q418

Data Integration déjà vu: Big Data Reinvigorates DI

Published By: SAS     Published Date: Jun 06, 2018
Data integration (DI) may be an old technology, but it is far from extinct. Today, rather than being done on a batch basis with internal data, DI has evolved to a point where it needs to be implicit in everyday business operations. Big data – of many types, and from vast sources like the Internet of Things – joins with the rapid growth of emerging technologies to extend beyond the reach of traditional data management software. To stay relevant, data integration needs to work with both indigenous and exogenous sources while operating at different latencies, from real time to streaming. This paper examines how data integration has gotten to this point, how it’s continuing to evolve and how SAS can help organizations keep their approach to DI current.
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SAS

Data Integration déjà vu: Big Data Reinvigorates DI

Published By: SAS     Published Date: Aug 28, 2018
Data integration (DI) may be an old technology, but it is far from extinct. Today, rather than being done on a batch basis with internal data, DI has evolved to a point where it needs to be implicit in everyday business operations. Big data – of many types, and from vast sources like the Internet of Things – joins with the rapid growth of emerging technologies to extend beyond the reach of traditional data management software. To stay relevant, data integration needs to work with both indigenous and exogenous sources while operating at different latencies, from real time to streaming. This paper examines how data integration has gotten to this point, how it’s continuing to evolve and how SAS can help organizations keep their approach to DI current.
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SAS

Digital reinvention - Trust, transparency and technology in the insurance world of tomorrow

Published By: IBM     Published Date: May 27, 2014
If insurers want to succeed in today's digital world, they need to create experiences and business models that are orchestrated, symbiotic, contextual and cognitive.
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ibm, big data, insurance, digital insurer, business model, insurance industry, technology, integration, social business, it management
    
IBM

Embedded Analytics Vendor Selection Guide

Published By: Pentaho     Published Date: Aug 22, 2016
This white paper covers six guidelines product leaders should explore during their embedded analytics evaluation.
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big data, data integration, bi systems, hadoop
    
Pentaho

Experience Oracle Cloud Integration for Free

Published By: Oracle     Published Date: Feb 21, 2018
Get Started with Oracle Cloud for Free $300 in free credits Build production-ready workloads by using a variety of cloud services including databases, compute, containers, IoT, big data, API management, integration, chatbots, and many more
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Oracle
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